Mapping and Analysis for Public Safety: Research
MAPS strives to maintain a high level of activity in both intramural and extramural research. Recent topics have included spatial data analysis, data sharing, offender travel behavior, and geographic profiling.
Spatial data analysis
Spatial data analysis utilizes statistical analysis methods that address specific issues relating to spatial data, including spatial dependence (autocorrelation) and spatial heterogeneity. These issues run counter to traditional statistical assumptions of heterogeneity and independence of sample data. If these issues are ignored, then analysis results might not be valid. In combining the powerful tools of GIS to integrate and manipulate spatial data with rigorous statistical methods, spatial data analysis shows great promise for criminology, criminal justice, and law enforcement research and practice.
MAPS has conducted in-house research that applies spatial data analysis methods. For example, one of the in-house studies is using Geographically Weighted Regression to explore the effect of religious institution density on homicide rates and to explain the impact of informal social control at the local level. Another study is using spatial regression to understand how the mass incarceration of criminals over the past 20 years is affecting neighborhoods.